The present invention relates to chromatography and, more particularly, to a system and method providing for mathematical correction of systematic baseline errors in chromatograms.
While having a broad range of applications, the present invention arose in the context of liquid chromatography systems using ultraviolet and visible light spectral analysis in the generation of chromatograms. One challenge faced by such chromatography systems is that systematic errors in the spectra, introduced by solvents and other sources, interfere with analysis of peak shape and component identification. A major objective of the present invention is to provide a flexible mathematical method for minimizing the effects of such systematic errors in chromatographic analysis.
Liquid chromatography typically involves separation of the components of a sample mixture by movement of a solvent mobile phase over a solid stationary phase in a chromatograph column. Each mixture component is partitioned according to a characteristic "partition coefficient" between the phases, depending on the solvent or solvent mixture in the column at the time. As the mobile phase moves past the stationary phase, repeated adsorption and desorption of the component occurs at a rate determined chiefly by its ratio of distribution between the two phases. If the partition coefficients for the different mixture components are sufficiently different, the components exit the effluent end of the column in a series of bands which, theoretically, can be analyzed to determine the identity and original concentration of each mixture component.
A spectrometer can be used to analyze the eluting components by generating a chromatogram comprised of a series of spectra. Typically, a chromatogram is characterized by a series of peaks, each peak ideally representing a gradually rising and declining magnitude of a pure spectral component traceable to an individual mixture component. Theoretically, by comparing the detected spectra of a peak with known spectra for various compounds, the component can be identified. By integrating each identified component over its corresponding peaks, the relative concentrations of the components in the original mixture can be determined, at least in the ideal.
Inevitably, errors in the chromatogram adversely affect determination of component identity and concentration. Error can include both random and systematic errors, the present invention addressing the latter. Systematic errors include those with components which have a constant spectral shape but vary in magnitude, resembling the component spectra themselves in this regard. Most systematic errors however are characterized by wider temporal distribution than component peaks.
Systematic errors are introduced as a matter of course as raw spectral data reflect the spectra of one or more solvents of the mobile phase as well as the mixture components. There are additional sources of systematic errors, including changes in spectral absorbance due to temperature or other effects, variations in spectrometer lamp intensity and color, and variations in the spectrometer detector sensitivity.
Systematic errors due to solvent spectral absorbance are usually addressed by subtracting a spectral component attributed to one or more solvents from a chromatogram. This can be a relatively simple procedure where a single solvent is involved. However, more complex procedures use multiple solvents in time-varying ratios to accommodate complex mixtures with components having a wide range of solvent characteristics. In these more complex cases, "subtraction" involves subtracting the right components in the right concentrations at the right times.
In practice it is difficult to know what solvents are eluting in what concentrations at any given time. Irregularities in the pumping and mixing apparatus used to introduce solvent mixtures into the chromatographic column can create unintended transients and fluctuations prior to introduction. Some of these time-varying effects can be addressed by subtracting blank run chromatograms. The solvents can be run through a column without the mixture so as to produce a solvent chromatogram. The solvent chromatogram can be subtracted from the chromatogram of interest to the contribution of the solvents to the spectral data.
However, the blank run approach does not address other time-varying systematic errors or interactive effects between the solvents and the mixture components. The blank-run approach is costly in that a new blank run is required for each solvent set up. In fact, several blank runs are needed to place a confidence level on the solvent chromatogram, since variations can occur from run to run. These variations constrain the extent to which blank run subtraction can address systematic errors in a chromatogram. In practice, even after correction by current methods, significant systematic errors remain in chromatographic data, especially when complex solvent systems are involved.
Another problem in determining the identity and relative concentrations of mixture components concerns the inability of a given solvent system to separate all mixture components. For example, if two or more mixture components have nearly the same partition coefficient between the mobile and stationary phases, they tend to elute at about the same time. The result is that the corresponding component peaks overlap.
The problem with overlap can be addressed mathematically. Simple mathematical peak-shape tests permit identification of chromatogram features representing overlapping component peaks. More complex mathematical procedures can be used to deconvolve overlapping peaks so that the identity and relative concentrations of the overlapping components can be determined.
The mathematical procedures used in peak-shape tests and deconvolution are highly sensitive to systematic errors. As chromatography is applied to increasingly complex mixtures, it becomes increasingly difficult to resolve all mixture components chemically. Accordingly, it is becoming increasingly important to remove systematic errors from chromatographic data so that mathematical methods can supplement more effectively the spectral analysis of mixtures.